DocumentCode :
3213119
Title :
A novel self-adaptive differential evolution algorithm for efficient design of multiplier-less low-pass FIR filter
Author :
Chandra, A. ; Chattopadhyay, S.
Author_Institution :
Dept. of Electron. & Telecommun. Eng., Bengal Eng. & Sci. Univ., Shibpur, India
fYear :
2011
fDate :
20-22 July 2011
Firstpage :
733
Lastpage :
738
Abstract :
Variety of real-world optimization problems can be successfully solved by employing a powerful technique, called Differential Evolution (DE) algorithm. The popularity of DE has grown tremendously since its inception as it includes a very few number of control parameters. However, the selection or tuning of these parameters plays a crucial role in determining the performance of the algorithm in terms of its convergence behaviour. In this paper, a novel Self-Adaptive DE (SADE) approach has been proposed for the de sign of a multiplier-less low-pass linear-phase FIR filter to improve the computational efficiency of the algorithm. For this purpose, the convergence behaviour of the SADE technique has been presented and it has been compared with that of traditional DE technique. Additionally, the performance of the SADE-optimized filter has been evaluated in terms of its magnitude response. The corresponding magnitude response for the DE-optimized filter has also been presented for comparison. It has been established that the proposed SADE algorithm outperforms the traditional DEfor this particular design problem.
Keywords :
FIR filters; computational complexity; convergence; evolutionary computation; linear phase filters; low-pass filters; SADE algorithm; SADE approach; SADE technique; SADE-optimized filter; computational efficiency; control parameters; convergence behaviour; magnitude response; multiplier-less low-pass FIR filter; multiplier-less low-pass linear-phase FIR filter design; parameter selection; parameter tuning; powerful technique; real-world optimization problems; self-adaptive DE approach; self-adaptive differential evolution algorithm; Convergence speed; Cost function; Differential Evolution (DE); Multiplier-less FIR filter; Weighting Factor;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
Conference_Location :
Chennai
Type :
conf
DOI :
10.1049/cp.2011.0460
Filename :
6143409
Link To Document :
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